Latest News Archive

Please select Category, Year, and then Month to display items
Previous Archive
14 December 2020
Prof Abdon Atangana
Prof Abdon Atangana is known for his work in developing a new fractional operator used to model real-world problems arising in the fields of science, technology, and engineering. He was recently awarded the TWAS Mohammad A. Hamdan Award by The World Academy of Sciences.

Prof Abdon Atangana, Professor of Applied Mathematics in the Institute for Groundwater Studies at the University of the Free State (UFS), was awarded the TWAS Mohammad A. Hamdan Award by The World Academy of Sciences for the advancement of science in developing countries.

It is the first time that the TWAS Mohammad A. Hamdan Award was bestowed. According to a statement issued by TWAS, this award is given for outstanding mathematical work carried out by a scientist working and living in Africa or the Arab region. It states that the award can be given for work in pure mathematics, applied mathematics, probability, or statistics. Prof Atangana received the award for his contribution to fractal mathematics and partial differential equations.

Making a difference in society

He is known for his research in developing a new fractional operator, the Atangana-Baleanu operator, which is used to model real-world problems. With this operator, he not only describes the rate at which something will change, but also account for disrupting factors that will help to produce better projections.

His work can be applied to make complicated predictions in the fields of science, technology, and engineering. His models can, for instance, help to predict the spread of infectious diseases among people in a settlement, forecasting the number of people who will be infected each day, the number of people who will recover, and the number of people who will die.

Prof Atangana’s models can also help to advise people drilling for water by predicting how groundwater is flowing in a complex geological formation. These are only two examples of how his work can be applied to make a difference in society.

The award from TWAS is the third prestigious commendation he has received in the past month. He was recently named as one of the top 1% scientists on the global Clarivate Web of Science list. His name also appeared on a global list of leading scientists published by Stanford University in the United States. The list is the result of a study published in PLOS Biology, a peer-reviewed open-access journal.

World’s most accomplished scientists

Honours awarded by TWAS and its partners are among the most prestigious for research in the developing world. They recognise outstanding achievements and contributions to science and acknowledge the best work by scientists from the global South.

TWAS, founded in 1983 by a group of scientists under the leadership of Pakistani physicist and Nobel laureate, Abdus Salam, believes that developing nations – by growing strength in science and engineering – will be able to address challenges such as hunger, disease, and poverty, through their knowledge and skills.

TWAS is represented in 100 countries, and of the more than a thousand elected fellows, 14 are Nobel laureates. Eighty-four percent of these fellows are from developing nations. TWAS fellows are also some of the world’s most accomplished scientists.

News Archive

Researcher works on finding practical solutions to plant diseases for farmers
2017-10-03

 Description: Lisa read more Tags: Plant disease, Lisa Ann Rothman, Department of Plant Sciences, 3 Minute Thesis,  

Lisa Ann Rothman, researcher in the Department of
Plant Sciences.
Photo: Supplied

 


Plant disease epidemics have wreaked havoc for many centuries. Notable examples are the devastating Great Famine in Ireland and the Witches of Salem. 

Plant diseases form, due to a reaction to suitable environments, when a susceptible host and viable disease causal organism are present. If the interactions between these three factors are monitored over space and time the outcome has the ability to form a “simplification of reality”. This is more formally known as a plant disease model. Lisa Ann Rothman, a researcher in the Department of Plant Sciences at the University of the Free State (UFS) participated in the Three Minute Thesis competition in which she presented on Using mathematical models to predict plant disease. 

Forecast models provide promise fighting plant diseases
The aim of Lisa’s study is to identify weather and other driving variables that interact with critical host growth stages and pathogens to favour disease incidence and severity, for future development of risk forecasting models. Lisa used the disease, sorghum grain mold, caused by colonisation of Fusarium graminearum, and concomitant mycotoxin production to illustrate the modelling process. 

She said: “Internationally, forecasting models for many plant diseases exist and are applied commercially for important agricultural crops. The application of these models in a South African context has been limited, but provides promise for effective disease intervention technologies.

Contributing to the betterment of society
“My BSc Agric (Plant Pathology) undergraduate degree was completed in combination with Agrometeorology, agricultural weather science. I knew that I wanted to combine my love for weather science with my primary interest, Plant Pathology. 
“My research is built on the statement of Lord Kelvin: ‘To measure is to know and if you cannot measure it, you cannot improve it’. Measuring the changes in plant disease epidemics allows for these models to be developed and ultimately provide practical solutions for our farmers. Plant disease prediction models have the potential ability to reduce the risk for famers, allowing the timing of fungicide applications to be optimised, thus protecting their yields and ultimately their livelihoods. I am continuing my studies in agriculture in the hope of contributing to the betterment of society.” 

We use cookies to make interactions with our websites and services easy and meaningful. To better understand how they are used, read more about the UFS cookie policy. By continuing to use this site you are giving us your consent to do this.

Accept